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Abstract
Objective To examine the longitudinal trajectories of maternal weight perception bias toward preschool children, to identify distinct trajectory groups, and to explore their associated sociodemographic characteristics. Methods In this longitudinal study, 176 mothers and their preschool children from eight public kindergartens in Shanghai were followed at three time points over a 2-year period, beginning in December 2020. Group-based trajectory modeling was used to identify trajectories of maternal weight perception bias, and multinomial logistic regression was performed to examine associated sociodemographic factors. Results Maternal misperception of children's weight status was predominantly characterized by underestimation. Across the three follow-up assessments, the proportions of accurate maternal perception were 64.2%, 63.1%, and 55.1%, respectively. Four trajectory groups were identified: persistent underestimation (n=29, 16.5%), underestimation-to-accurate perception (n=17, 9.6%), persistent accurate perception (n=88, 50.0%), and accurate perception-to-underestimation (n=42, 23.9%). Multinomial logistic regression showed that, compared with the persistent accurate perception group, a higher baseline BMI-for-age Z score (BAZ) was associated with a lower likelihood of persistent underestimation (OR=0.130, 95%CI: 0.059 - 0.289). In addition, compared with mothers of girls, mothers of boys were more likely to shift from accurate perception to underestimation (OR=4.793, 95%CI: 1.959 - 11.725). Conclusions Maternal weight perception bias toward preschool children follows distinct trajectories over time.Children's gender and early BAZ are important factors associated with trajectory patterns of maternal weight perception bias.
Keywords
overweight
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obesity
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weight perception
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perception bias
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preschool children
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group-based trajectory model
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SONG Xinyi, CHEN Yujia, QU Fangge, WEI Xiaoxue, TANG Xianqing, ZHU Daqiao.
Trajectories of maternal weight perception bias toward preschool children and associated sociodemographic characteristics.
ENG. Environ., 2026, 34 (7) : 749-753 DOI:10.11852/zgetbjzz2026-0058